Welcome to my storyboard for the computational musicology course. With this course 1 made 2 songs. I created these songs using the generative AI tool Stable Audio. I simply wrote a short prompt for each track to guide the style and mood.
Track 1
Prompt:
3 minutes Pixelwave, jazz fusion, retro 8-bit melodies, smooth synths, glitch effects, complex rhythms, futuristic vibes, melodic improvisation, digital textures, ambient soundscapes, quirky transitions
Track 2
Prompt:
Classical Grunge, raw grunge guitar, symphonic strings, orchestral arrangements, distorted power chords, melancholic melodies, classical structure, gritty atmosphere, dynamic contrast, emotional intensity.
This heatmap shows the normalized values of different features for 90 songs. Each tile’s color represents the scaled value (from 0 to 1) of a feature, making comparisons fair even when the original numbers differ a lot. Hover over a tile to see the real value. My tracks, “mees-k-1” and “mees-k-2”, are highlighted in red.
In conclusion, there is significant variance among the tracks produced by my peers. I look forward to sharing more detailed visualizations and insights as I continue exploring these musical features.